LoadCsv-v1

100%

✓ Published1🌍 Public

Last edited Jun 5, 2022

Created on Jun 5, 2022

Forked from LoadCsv

This example loads CSV data using `d3.csv`, processes each row to calculate a `duration` field, and filters out invalid entries where the end time precedes the start time. The processed data is then passed to a chart via `d3.select("#chart")` with a `.join()` operation that appends text elements. The code references the Iris Dataset as its source, though the actual CSV strings shown are placeholder example data. It demonstrates a reusable scatter plot pattern inspired by Mike Bostock’s "Towards Reusable Charts" and Observable’s selection-join technique.

AI-generated description

A reusable scatter plot inspired by Towards Reusable Charts and Observable: selection.join.

Shows the Iris Dataset.

MIT Licensed

Similar vizzes

Loading thumbnail…

LoadCsv

This example demonstrates how D3 loads and processes CSV data, specifically highlighting the behavior of `d3.csv` with a custom row-accessor function. The code defines an inline array that mimics CSV content, then uses `d3.csv` to parse it while trimming, lowercasing, and computing a derived `duration` field. Rows where the end value is not greater than the start value are filtered out. The processed result is logged to the console along with the column keys, showing which columns remain after transformation. It uses D3 v5’s promise-based `d3.csv` API and the `data.columns` property to inspect parsed fields.

JJimMaltby

83% match

Loading thumbnail…

Loading CSV

This example demonstrates how to load and display a CSV dataset using D3. It fetches the Iris Dataset from a remote URL and renders the parsed data as a JSON-formatted text block within the page. The code uses `d3.csv()` to asynchronously retrieve and parse the CSV file, then chains `.then()` to append a `<pre>` element to the body via `d3.select()`. The resulting output shows the structured data, making the loading and parsing process visible.

Bbio_sun

77% match

Loading thumbnail…

Fork of Loading Data

This example demonstrates loading and parsing the Iris Dataset from a CSV file using D3’s `csvParse` function, then rendering a single circle at a fixed position with the `scatterPlot` module. The visualization initializes with a loading state, fetches the data asynchronously, converts numerical columns to numbers, and triggers a re-render once data arrives. It uses D3 v7 selections and joins to manage the SVG and circle elements, with a minimal UI showing the data-loading process.

Ffloraho401

76% match

Loading thumbnail…

Loading CSV Data with D3

This example demonstrates how to load a CSV file into a web page using D3 v3’s `d3.csv` method. The page displays a static SVG canvas containing a blue line, a red rectangle, and a violet circle, while the CSV data for Chicago’s socioeconomic indicators is parsed into an array of JavaScript objects and logged to the browser console. No chart is rendered; the focus is solely on verifying successful asynchronous data loading and transformation.

JJasonMcGregor

76% match

Loading thumbnail…

Fork of Loading CSV

This example demonstrates how to load and display a CSV dataset using D3.js. It fetches the Iris Dataset from a remote URL and renders the raw data as formatted JSON text on the page. The visualization first uses D3’s `csv` function to asynchronously load the data, then chains a `.then()` callback to append a `<pre>` element to the body, converting the parsed data to a readable JSON string with `JSON.stringify`. The code relies on D3 v5’s `select` and `csv` APIs, showing a minimal workflow for ingesting tabular data and presenting it in the browser without any charting or interactive elements.

MM Hema

75% match

Loading thumbnail…

Load CSV

This example demonstrates how to load and parse a CSV file using D3.js v4. The page fetches the classic Iris dataset from a local CSV file and uses the `d3.csv` method with a row-accessor function to convert numeric string values into numbers for all four measurement columns (petalLength, petalWidth, sepalLength, sepalWidth). The parsed data is then logged to the browser console. This simple yet essential example highlights D3's data-loading capabilities, showing how raw CSV text is transformed into an array of JavaScript objects with properly typed fields, ready for further visualization or analysis.

335degrees

75% match

Loading thumbnail…

Loading Data

This example demonstrates how to load and parse a CSV file in D3.js, displaying the raw parsed data as a stringified JSON object in a `<pre>` element. The visualization uses a state management pattern with a `setState` function to handle asynchronous data loading, initially showing a "LOADING" placeholder. It fetches `data.csv`, parses it with `d3.csvParse`, and converts numeric columns to numbers before updating the display. The Iris flower dataset is used as the data source, with the rendering approach being a simple text-based output rather than a graphical chart.

IIshaChid76

75% match

Loading thumbnail…

Loading and Parsing CSV data

This example demonstrates how to load and parse CSV data using D3.js, displaying a summary of the loaded dataset in a large text element. It fetches the classic Iris dataset from a GitHub gist via `d3.csv`, then reports the file size in kilobytes, row count, and column count. The visualization also includes commented-out alternative code using the Fetch API with `async/await` and `d3.csvParse`, highlighting two approaches for handling CSV data in D3 v7 within a minimal HTML page.

Sstephanie0215

75% match